Transactions on large-scale data- and knowledge-centered systems LI : special issue on data management - principles, technologies and applications / Abdelkader Hameurlain, A Min Tjoa, Esther Pacitti, Zoltan Miklos (eds.).
2022
QA76.9.D3
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Title
Transactions on large-scale data- and knowledge-centered systems LI : special issue on data management - principles, technologies and applications / Abdelkader Hameurlain, A Min Tjoa, Esther Pacitti, Zoltan Miklos (eds.).
ISBN
9783662661116 (electronic bk.)
366266111X (electronic bk.)
9783662661109
3662661101
366266111X (electronic bk.)
9783662661109
3662661101
Published
Berlin : Springer, [2022]
Copyright
©2022
Language
English
Description
1 online resource (ix, 137 pages) : illustrations (chiefly color).
Item Number
10.1007/978-3-662-66111-6 doi
Call Number
QA76.9.D3
Dewey Decimal Classification
005.74
Summary
The LNCS journal Transactions on Large-scale Data and Knowledge-centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. This, the 51th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains four fully revised and extended papers selected from the 37th conference on Data Management - Principles, Technologies and Applications, BDA 2021. The topics cover a wide range of timely data management research topics on threats modelling, RDF schema generation, data coverage optimization, data quality and storage on synthetic DNA.
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Includes author index.
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Series
Lecture notes in computer science ; 13410.
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Table of Contents
Threats Modeling And Anomaly Detection In The Behaviour Of A System - A Review Of Some Approaches
Incremental Schema Generation for Large and Evolving RDF Sources
Optimizing Data Coverage and Significance in Multiple Hypothesis Testing on User Groups
Efficiently identifying disguised missing values in heterogeneous, text-rich data
Digital Preservation with Synthetic DNA. .
Incremental Schema Generation for Large and Evolving RDF Sources
Optimizing Data Coverage and Significance in Multiple Hypothesis Testing on User Groups
Efficiently identifying disguised missing values in heterogeneous, text-rich data
Digital Preservation with Synthetic DNA. .